The Effect of Near-Term Policy Choices on Long-Term Greenhouse Gas Transformation Pathways

Steven C. Isley, Robert J. Lempert, Steven W. Popper, Raffaele Vardavas

ResearchPosted on rand.org Nov 23, 2015Published in: Global Environment Change, v. 34, Sep. 2015, p. 147-158

To successfully limit climate change, today's greenhouse gas mitigation policies should encourage reductions that will continue for decades. History suggests, however, that some policy reforms lead to societal changes that persist over the long-term while others fade without long-term effect. Current climate policy literature provides little guidance on how today's policy choices can successfully shape long-term emission reduction paths. To address such questions, this paper introduces a new agent-based, game theoretic model designed to compare how near-term choices regarding alternative policy architectures influence long-term emission reduction trajectories. Drawing on political science literature that identifies the characteristics of policies that persist over time, this simulation for the first time integrates the co-evolution of an industry sector, its technology base, and the shifting political coalitions that influence the future stringency of the government's emission reduction policies--all as influenced by the initial choice of policy architecture. An exploratory modeling analysis that represents deeply uncertain phenomena such as the future potential for innovation and the behavior of future governments draws policy-relevant conclusions from this model. The analysis finds that near-term choices regarding the architecture of a carbon pricing policy may affect long-term decarbonization rates significantly. In particular, such rates are higher if program revenues are returned to firms in proportion to their market share, thus, creating a political constituency for continuing the carbon pricing policy. More generally, the analysis provides a framework for considering how near-term policy choices can affect long-term emission transformation pathways within integrated assessment models.

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Document Details

  • Availability: Non-RAND
  • Year: 2015
  • Pages: 12
  • Document Number: EP-50876

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